summary.mbnma.network() returns valid minimum doses per agentparallel=TRUE and added a warning when pd is set to "pd.kl" or "popt" for these models.summary() for multiple dose-response function modelsfun="rcs") in mbnma.run()mbnma.run() to allow relaxing of the consistency assumption. This can be used to test its validity.cumrank() added for cumulative ranking plots. Also calculates SUCRA values for each agent and dose-response parameterautojags options added for mbnma.run() to allow users to run models until they converge (convergence defined by Rhat)rank.mbnma() also calculates cumulative ranking probabilities and stores them in cum.matrixgetjagsdata() contains studyID and has been added to mbnma objectsdevplot() and fitplot()plot.nodesplit() scales y-axis if density is >50 times larger in panel with highest density than in panel with lowest density. This improves legibility of the graph.class("nodesplit")mbnma.nodesplit() includes potential splits via dose-response curve and direct and indirect evidence contributions are calculated simultaneously in the same model.mbnma.nodesplit() and nma.nodesplit()plot.mbnma.network()psoriasis and ssri datasets to packagecrayon package to neaten printed console outputsfun in mbnma.run()) so that multiple functions can be modelled simultaneously. Some downstream package functions still may not yet work with these models though.mbnma.network objects returned from plot.mbnma.network now have specific igraph attributes assigned to them, which can be easily changed by the user.user.fun now takes a formula as an argument (for example ~ (beta.1 * dose) + (beta.2 * dose^2)) rather than a string.plot.mbnma.network() now uses a layout argument that takes an igraph layout function instead of layout_in_circle (which was a logical argument). This allows any igraph layout to be plotted rather than just a circle (e.g. igraph::as_star())if {class(x)=="matrix"} statements to if {is.matrix(x)} to address R development changespd="plugin"), or Kullback-Leibler divergence (pd="pd.kl")parallel=TRUE in mbnma.run() (or wrapper functions) now properly runs JAGS in parallel on multiple cores.mbnma.network in their output rather than just treatment and agent names.nma.nodesplit() that prevented the model running if disconnected treatments were included in the analysis (drop.discon=FALSE)Welcome to MBNMAdose. Ready for release into the world. I hope it can be of service to you! For time-course MBNMA, also check out the sister package, MBNMAtime.